| Type: | Package |
| Title: | Small Area Estimation for Continuous Zero Inflated Data |
| Version: | 0.2.0 |
| Maintainer: | Josh Yamamoto <joshuayamamoto5@gmail.com> |
| Description: | Provides functionality to fit a zero-inflated estimator for small area estimation. This estimator is a combines a linear mixed effects regression model and a logistic mixed effects regression model via a two-stage modeling approach. The estimator's mean squared error is estimated via a parametric bootstrap method. Chandra and others (2012, <doi:10.1080/03610918.2011.598991>) introduce and describe this estimator and mean squared error estimator. White and others (2024+, <doi:10.48550/arXiv.2402.03263>) describe the applicability of this estimator to estimation of forest attributes and further assess the estimator's properties. |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| LazyData: | true |
| Imports: | dplyr, lme4, purrr, progressr, furrr, future, rlang, Rcpp |
| RoxygenNote: | 7.3.1 |
| Suggests: | testthat (≥ 3.0.0) |
| Config/testthat/edition: | 3 |
| Depends: | R (≥ 4.1.0) |
| LinkingTo: | Rcpp, RcppEigen |
| URL: | https://harvard-ufds.github.io/saeczi/ |
| NeedsCompilation: | yes |
| Packaged: | 2024-06-06 14:36:29 UTC; joshuayamamoto |
| Author: | Josh Yamamoto [aut, cre], Dinan Elsyad [aut], Grayson White [aut], Julian Schmitt [aut], Niels Korsgaard [aut], Kelly McConville [aut], Kate Hu [aut] |
| Repository: | CRAN |
| Date/Publication: | 2024-06-06 14:50:02 UTC |
FIA Population Level Auxiliary Data for Oregon
Description
FIA Population Level Auxiliary Data for Oregon
Usage
pop
Format
An object of class data.frame with 10060 rows and 10 columns.
Fit a zero-inflation estimator.
Description
Fit a zero-inflation estimator.
Usage
saeczi(
samp_dat,
pop_dat,
lin_formula,
log_formula = lin_formula,
domain_level,
B = 100L,
mse_est = FALSE,
estimand = "means",
parallel = FALSE
)
Arguments
samp_dat |
A data.frame with domains, auxiliary variables, and the response variable of a sample |
pop_dat |
A data.frame with domains and auxiliary variables of a population. |
lin_formula |
Formula. Specification of the response and fixed effects of the linear regression model |
log_formula |
Formula. Specification of the response and fixed effects of the logistic regression model |
domain_level |
String. The column name in samp_dat and pop_dat that encodes the domain level |
B |
Integer. The number of bootstraps to be used in MSE estimation. |
mse_est |
Logical. Whether or not MSE estimation should happen. |
estimand |
String. Whether the estimates should be 'totals' or 'means'. |
parallel |
Logical. Should the MSE estimation be computed in parallel |
Value
An object of class 'zi_mod' with defined 'print()' and 'summary()' methods. The object is structured like a list and contains the following elements:
* call: The original function call
* res: A data.frame containing the estimates and mse estimates
* lin_mod: The modeling object used to fit the original linear model
* log_mod: The modeling object used to fit the original logistic model
Examples
data(pop)
data(samp)
lin_formula <- DRYBIO_AG_TPA_live_ADJ ~ tcc16 + elev
result <- saeczi(samp_dat = samp,
pop_dat = pop,
lin_formula = lin_formula,
log_formula = lin_formula,
domain_level = "COUNTYFIPS",
mse_est = FALSE)
FIA sample data for Oregon
Description
FIA sample data for Oregon
Usage
samp
Format
An object of class tbl_df (inherits from tbl, data.frame) with 1494 rows and 11 columns.